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    BLEU Score

    AI fundamentals & modelsBLUEBilingual Evaluation UnderstudyBLEU metric
    Editorially reviewed on: 1 source
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    The short answer · 15 words

    In short

    Automatic metric for evaluating machine-generated translations based on the match of n-grams with reference translations.

    Flow-alerta.cab (2026): BLEU Score. https://flow-alerta.cab/en/glossar/bleu-score. Editorially reviewed on: 09 October 2026.

    How much detail would you like?

    Practical

    Historically important evaluation metric for machine translation. For modern generative systems, it should be complemented by semantic and human evaluation.

    Example scenario: Two translation models are compared on the same test set and with the same reference translations based on their BLEU score.

    Use only for suitable translation or text tasks and always supplement with domain-specific quality criteria.

    At a glance

    Core
    BLEU compares n-grams of a generated translation with one or more references, uses modified n-gram precision, and a length penalty for too short outputs. The metric was developed for corpus comparisons and does not measure factual fidelity or complete semantic equivalence.
    Use
    Historically important evaluation metric for machine translation. For modern generative systems, it should be complemented by semantic and human evaluation.
    Example
    Example scenario: Two translation models are compared on the same test set and with the same reference translations based on their BLEU score.
    Limits
    Compare BLEU between different data sets; over-interpret individual sentences; equate high score with factual fidelity; ignore tokenization and implementation details.

    In context

    BERTScore

    Automatic evaluation metric for generated text that compares token similarities based on contextual embeddings instead of just exact word matches.

    Questions about this term

    Is a higher BLEU score better?

    Within the same clean evaluation usually yes.

    Does BLEU measure meaning completely?

    No.

    Does BLEU need reference texts?

    Yes.

    All details and background

    BLEU compares n-grams of a generated translation with one or more references, uses modified n-gram precision, and a length penalty for too short outputs. The metric was developed for corpus comparisons and does not measure factual fidelity or complete semantic equivalence.

    ELI5 – Explained simply

    BLEU checks how much word groups of a translation overlap with good reference translations and punishes conspicuously short results.

    Why it matters in practice

    Historically important evaluation metric for machine translation. For modern generative systems, it should be complemented by semantic and human evaluation.

    Example

    Example scenario: Two translation models are compared on the same test set and with the same reference translations based on their BLEU score.

    Pitfalls and limits

    • Compare BLEU between different data sets; over-interpret individual sentences; equate high score with factual fidelity; ignore tokenization and implementation details.

    Origin & history

    Papineni, Roukos, Ward and Zhu introduced BLEU at ACL in 2002 as an automatic evaluation method for machine translation.

    Use in mid-sized companies

    • Use only for suitable translation or text tasks and always supplement with domain-specific quality criteria.

    Related terms

    Matching Flow-alerta service

    AI opportunity analysis & roadmapAI consulting: AI potential analysis & roadmap on tasks, data and prerequisites of a possible first AI use case.

    Matching tool / use case

    View use casesUse Case: standardized comparison of two translation models on the same test set.

    Sources

    Quellenprüfung: 09.10.2026. Definition und dokumentierte Einordnung abgeglichen; Beispiele beschreiben mögliche Anwendungen.

    Editorially reviewed on:

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